K-AgentPay: Korea travel & K-pop data

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does add real behavioral context: the data is live and the call is metered at '10 free calls/day'. However it says nothing about what happens when the quota is exhausted, whether responses are cached, or the refresh cadence of the 'live' figures.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, zero filler, with the resource and scope front-loaded and the quota constraint placed last. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must convey the return shape, and it does (waiting minutes and queue per hall, plus the shortest hall). The main remaining gap is update frequency/coverage of the 'live' data, which an agent might need to judge staleness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is one optional parameter (lang) with 100% schema description coverage and an enum, so the schema already documents it fully; the description adds nothing about language handling. Baseline 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (Incheon Airport departure-hall wait times and queues) with explicit scope (per hall T1/T2, plus the shortest hall) and a data-freshness qualifier ('Live'). No sibling tool covers airport queues, so an agent can tell it apart from seoul_subway_now or seoul_now without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the description ('departure-hall waiting minutes') but there is no explicit when-to-use statement, no prerequisites, and no guidance on alternatives or when this is the wrong tool. Adequate but leaves routing entirely to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it discloses one genuinely useful behavioral trait: a hard rate limit of 10 free calls/day, which an agent should plan around. Beyond that it says nothing about authentication, pagination, result volume, whether the date is inclusive, or the return shape, leaving substantial gaps for a data-retrieval tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with the scope stated first and no filler. It is slightly telegraphic ('from a date') but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paginated-looking data-listing tool with no output schema and no annotations, the description should say more about what comes back (fields, count limits, ordering) and how the free tier behaves once exhausted. Those essentials are missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

At 50% schema description coverage, only 'lang' is documented in the schema; the description covers 'from' but mostly by repeating the YYYYMMDD format already encoded as pattern ^\d{8}$. It does not clarify whether the date is inclusive, how far forward results extend, or the ordering of returned events, so it only marginally compensates for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (festivals and events in Korea) and a starting-point parameter, so an agent knows it is a listing tool for Korean festival data. It does not, however, distinguish itself from siblings such as kpop_new_concerts or request_korea_data, which could plausibly return overlapping event data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to choose this tool over the other Korea-data siblings, nor any exclusions (e.g. 'only festivals, not concerts'). The '10 free calls/day' note constrains volume but is a quota, not usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose one real behavioral trait: the '10 free calls/day' quota. However, it says nothing about return shape, pagination, auth requirements, or what 'updated' means for a previously-listed concert.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single compact sentence with the resource and recency filter front-loaded and the rate limit appended. Very little waste, though 'optional artist' is a slightly loose gloss for a parameter literally named `q`.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no annotations, so the description is the only source of behavior. It covers purpose, the date filter, and quota, but omits result fields, result ordering, and whether the query matches artist name, venue, or free text.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33% (lang is the sole documented param), so the description must compensate. It supplies the YYYYMMDD format and the 7-day default for `since`, and maps 'optional artist' to `q`, leaving only edge semantics of the free-text query unstated.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (Korea concerts) with a meaningful scope qualifier: 'newly registered or updated since a date'. This is distinguishable from kpop_search by the recency framing, though it does not name that sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use, when-not-to-use, or alternative routing is given. An agent must infer that this is for recently-changed concerts rather than general K-pop lookups; nothing points to kpop_search or korea_festivals as the alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It does disclose useful traits: no cost ('Free.'), a hard 6-month temporal window, any-language query support, and that the return is concert ids. It omits auth requirements, result limits/pagination, and what an agent must do with an id afterwards, which matters for a tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three compact clauses with zero waste; cost, purpose, scope and return type are all front-loaded and skimmable. Nothing restates the schema or the name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter, no-output-schema lookup tool this covers the essentials — what it searches, over what window, and that it returns ids. However, with no output schema the description is the only place to say how many ids come back or whether a follow-up call is needed, and it stays silent on both.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both q ('artist or title') and lang ('answer language: en/ja/ko'), setting the baseline at 3. The description's 'any language' adds a marginal nuance that queries may be issued in any language, but it does not explain the interaction between query language and the lang answer-language parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Search) plus resource (K-pop / pop concerts in Korea) and a precise scope (next 6 months, by artist or title). It clearly separates itself from a bare listing tool, but it never names or contrasts the obvious sibling kpop_new_concerts, leaving sibling differentiation to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The leading 'Free.' signal hints this is the no-cost option and 'by artist or title' implies a keyword-lookup use case, so usage is implied rather than stated. There is no explicit when-to-use vs kpop_new_concerts or korea_festivals, and no stated exclusions (e.g., what falls outside the 6-month window).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose two useful traits: the request is free, and fulfillment is prioritized by demand rather than immediate. It never states what the call returns (confirmation? the data? nothing) or that the result is not instant, leaving the async submission nature only implied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with zero filler; "Free." is front-loaded and the prioritization rule follows immediately. It is appropriately sized for a trivial request tool, though the one-word opener carries little semantic weight.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool with no output schema, the purpose and the demand-based prioritization are covered. Missing are the expected response from the call and any minimal guidance on describing the requested data, which an agent needs to fill the want field well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the schema documents nothing about the two parameters. The description's "ask for Korea data" loosely maps to want, but adds no guidance on format, specificity, or what useCase should contain, so it fails to compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete action (request Korea data not yet covered) and a consequence (most requested gets added first), which clearly distinguishes it from the data-returning siblings like korea_festivals and seoul_places. It does not explicitly say it is a suggestion/feedback submission, but the intent is inferable in one read.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

"these tools don't cover yet" implies the triggering condition (use only when no sibling supplies the data), and no sibling is named as an alternative because the trigger is coverage. However, it gives no explicit exclusion such as not using it for data that already exists, and "these tools" is vague about scope.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose a real behavioral constraint: '10 free calls/day.' However, it says nothing about authentication needs, error behavior, whether all Seoul places are covered, or how stale the 'live' data is, leaving meaningful gaps for a tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact sentences, front-loaded with the returned data and finished with the operational constraint. Nothing is redundant and the rate limit is stated rather than buried.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description usefully enumerates what comes back (current crowd, 12-hour forecast, weather) and flags the call quota. It is close to complete for a simple read tool, missing only input-format guidance for place and any coverage caveats.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50%: lang is documented in the schema while place has only length bounds. The description partly compensates by giving example values ('Myeongdong, Hongdae') for place, but it never mentions the lang parameter or the accepted place-name format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the exact resource (a Seoul place) and the three data points returned: live crowd level, 12-hour crowd forecast, and weather. That is enough to separate it from siblings like seoul_subway_now and incheon_airport_wait, though it never explicitly contrasts itself with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied by the word 'now' and the 'live crowd level' framing — an agent can infer this is for checking current conditions before visiting a place. There is no explicit when-to-use/when-not-to-use statement and no named alternative among the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the call is free and how many records are returned (121), which is useful behavioral context, but says nothing about read-only nature, side effects, or the shape of the response.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short fragments with no filler. However, 'Free.' is front-loaded despite being the least decision-relevant fact, pushing the actual scope statement to second position.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description should convey what the caller receives; '121 Seoul places (with codes)' gives a rough shape but not the fields per place or the encoding of the codes. Adequate for a zero-required-param lookup, but thin.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single `lang` parameter is 100% documented in the schema with its enum values and default. The description adds no meaning beyond that, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

It names the resource (the 121 Seoul places) and their key attribute (codes), and ties them to the sibling tool seoul_now that consumes them. The verb is implied rather than stated ('list/retrieve'), but the resource and scope are specific enough to distinguish it from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'accepted by seoul_now' implies the intended workflow (fetch valid place codes before calling seoul_now), but it never states when to use this tool versus seoul_now itself or seoul_trip_pack. Usage is inferable, not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It does disclose a genuinely useful behavioral trait the schema does not: a quota of 10 free calls/day. However, it says nothing about what is returned (line, direction, countdown), whether station names must match exactly, or failure behavior for unknown stations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact sentences with the core capability front-loaded and the quota constraint following. Every clause earns its place; nothing is padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter lookup with no output schema, the description covers the essentials (language support, rate limit) but omits the return shape and any hint about station-name matching, leaving an agent to guess how results come back.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% – the 'lang' param is documented but 'station' has no schema description. The description compensates by stating the station can be given in English, Japanese or Korean, which is exactly the missing semantic detail for that parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Next trains at a Seoul subway station') plus a real-time scope ('right now'), which is clear enough to distinguish it from the broader sibling seoul_now. It does not explicitly name a sibling to contrast against, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'right now' phrasing implies a real-time lookup use case, but there is no explicit when-to-use or when-not-to-use guidance, nor any mention of the sibling tools (seoul_now, seoul_places) that an agent might confuse this with.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It usefully discloses the scope of the returned bundle and hints at a constraint ('paid only'), but leaves the nature of that constraint unclear — is the payment for tickets or for the call itself? It also says nothing about permissions, caching, or data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, front-loaded with the contents of the pack rather than burying them. The em-dash clause is slightly awkward and the 'paid only' fragment muddies the structure, but there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter read tool with no output schema, the enumeration of bundle contents substitutes well for a return-value description. The remaining gap is the unclear 'paid only' clause, which an agent might misread as an access restriction on the tool itself.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter is already documented as 'concert id from kpop_search', so the schema does the heavy lifting. The description adds no format, provenance, or lookup details beyond what the schema states; baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific resource (a Seoul concert trip pack) and enumerates its contents — tickets, venue, last trains, crowd, hotels/food — which clearly separates it from kpop_search or seoul_places. The verb is weaker ('returns how to buy it'), and 'paid only' is ambiguous about whether the tool is gated or the tickets are, so it falls short of a clean verb+resource statement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: the schema notes the id comes from kpop_search, so an agent can infer this is the follow-up aggregation step after finding a concert. Nothing states when to pick this over siblings like kpop_new_concerts, seoul_places, or seoul_now, and no exclusions or prerequisites are given in the description itself.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.